Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations4287
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory368.5 KiB
Average record size in memory88.0 B

Variable types

Numeric8
DateTime2
Text1

Alerts

frequency is highly overall correlated with last_visit and 5 other fieldsHigh correlation
last_visit is highly overall correlated with frequency and 1 other fieldsHigh correlation
monatary is highly overall correlated with frequency and 4 other fieldsHigh correlation
recency is highly overall correlated with frequency and 5 other fieldsHigh correlation
total_items is highly overall correlated with frequency and 4 other fieldsHigh correlation
total_quantity is highly overall correlated with frequency and 4 other fieldsHigh correlation
total_unique_items is highly overall correlated with frequency and 4 other fieldsHigh correlation
monatary is highly skewed (γ1 = 24.25011359)Skewed
total_quantity is highly skewed (γ1 = 20.24345495)Skewed
customer_id has unique valuesUnique

Reproduction

Analysis started2024-10-01 10:55:14.009198
Analysis finished2024-10-01 10:55:41.027806
Duration27.02 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct4287
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15355.474
Minimum12346
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:41.311805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum12346
5-th percentile12696.6
Q113889.5
median15361
Q316839.5
95-th percentile17988.7
Maximum18287
Range5941
Interquartile range (IQR)2950

Descriptive statistics

Standard deviation1700.5656
Coefficient of variation (CV)0.11074654
Kurtosis-1.1938072
Mean15355.474
Median Absolute Deviation (MAD)1477
Skewness-0.016714419
Sum65828915
Variance2891923.2
MonotonicityStrictly increasing
2024-10-01T13:55:41.843804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18287 1
 
< 0.1%
12346 1
 
< 0.1%
12347 1
 
< 0.1%
12348 1
 
< 0.1%
12349 1
 
< 0.1%
12351 1
 
< 0.1%
12352 1
 
< 0.1%
12353 1
 
< 0.1%
12355 1
 
< 0.1%
12356 1
 
< 0.1%
Other values (4277) 4277
99.8%
ValueCountFrequency (%)
12346 1
< 0.1%
12347 1
< 0.1%
12348 1
< 0.1%
12349 1
< 0.1%
12351 1
< 0.1%
12352 1
< 0.1%
12353 1
< 0.1%
12355 1
< 0.1%
12356 1
< 0.1%
12357 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18286 1
< 0.1%
18285 1
< 0.1%
18284 1
< 0.1%
18283 1
< 0.1%
18281 1
< 0.1%
18280 1
< 0.1%
18279 1
< 0.1%
18278 1
< 0.1%
18277 1
< 0.1%

monatary
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4225
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2034.552
Minimum1.55
Maximum349164.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:42.322817image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.55
5-th percentile111.509
Q1308.4
median710.98
Q31723.245
95-th percentile6173.159
Maximum349164.35
Range349162.8
Interquartile range (IQR)1414.845

Descriptive statistics

Standard deviation8821.9698
Coefficient of variation (CV)4.3360749
Kurtosis777.17745
Mean2034.552
Median Absolute Deviation (MAD)503.13
Skewness24.250114
Sum8722124.4
Variance77827151
MonotonicityNot monotonic
2024-10-01T13:55:43.095287image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
102 3
 
0.1%
165 3
 
0.1%
131.25 2
 
< 0.1%
405 2
 
< 0.1%
79.9 2
 
< 0.1%
262.4 2
 
< 0.1%
317.76 2
 
< 0.1%
209.4 2
 
< 0.1%
307.95 2
 
< 0.1%
429 2
 
< 0.1%
Other values (4215) 4265
99.5%
ValueCountFrequency (%)
1.55 1
< 0.1%
2.95 1
< 0.1%
3.75 1
< 0.1%
6.3 1
< 0.1%
7.49 1
< 0.1%
9.7 1
< 0.1%
10.55 1
< 0.1%
10.95 1
< 0.1%
13.52 1
< 0.1%
13.92 1
< 0.1%
ValueCountFrequency (%)
349164.35 1
< 0.1%
248396.5 1
< 0.1%
186849 1
< 0.1%
140378.89 1
< 0.1%
131443.19 1
< 0.1%
84541.17 1
< 0.1%
83282.93 1
< 0.1%
80489.21 1
< 0.1%
65500.07 1
< 0.1%
57912.03 1
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4378353
Minimum1
Maximum183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:43.852652image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile13
Maximum183
Range182
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.9617785
Coefficient of variation (CV)1.794068
Kurtosis149.44434
Mean4.4378353
Median Absolute Deviation (MAD)1
Skewness9.8882849
Sum19025
Variance63.389917
MonotonicityNot monotonic
2024-10-01T13:55:44.455653image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1409
32.9%
2 807
18.8%
3 522
 
12.2%
4 378
 
8.8%
5 240
 
5.6%
6 188
 
4.4%
7 154
 
3.6%
8 110
 
2.6%
9 79
 
1.8%
10 68
 
1.6%
Other values (53) 332
 
7.7%
ValueCountFrequency (%)
1 1409
32.9%
2 807
18.8%
3 522
 
12.2%
4 378
 
8.8%
5 240
 
5.6%
6 188
 
4.4%
7 154
 
3.6%
8 110
 
2.6%
9 79
 
1.8%
10 68
 
1.6%
ValueCountFrequency (%)
183 1
< 0.1%
155 1
< 0.1%
135 1
< 0.1%
120 1
< 0.1%
109 1
< 0.1%
97 1
< 0.1%
94 1
< 0.1%
91 2
< 0.1%
89 1
< 0.1%
86 1
< 0.1%

last_visit
Real number (ℝ)

HIGH CORRELATION 

Distinct300
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.63261
Minimum1
Maximum374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:45.023649image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q118
median52
Q3136
95-th percentile302.7
Maximum374
Range373
Interquartile range (IQR)118

Descriptive statistics

Standard deviation96.51785
Coefficient of variation (CV)1.0649351
Kurtosis0.64998212
Mean90.63261
Median Absolute Deviation (MAD)40
Skewness1.2950717
Sum388542
Variance9315.6954
MonotonicityNot monotonic
2024-10-01T13:55:45.712651image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 97
 
2.3%
15 93
 
2.2%
1 90
 
2.1%
8 79
 
1.8%
4 74
 
1.7%
10 73
 
1.7%
17 71
 
1.7%
9 67
 
1.6%
11 62
 
1.4%
5 62
 
1.4%
Other values (290) 3519
82.1%
ValueCountFrequency (%)
1 90
2.1%
2 97
2.3%
3 61
1.4%
4 74
1.7%
5 62
1.4%
7 42
1.0%
8 79
1.8%
9 67
1.6%
10 73
1.7%
11 62
1.4%
ValueCountFrequency (%)
374 7
0.2%
373 9
0.2%
372 8
0.2%
371 6
0.1%
370 1
 
< 0.1%
369 7
0.2%
368 10
0.2%
367 7
0.2%
366 9
0.2%
365 8
0.2%

recency
Real number (ℝ)

HIGH CORRELATION 

Distinct373
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.34173
Minimum1
Maximum374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:46.080648image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median107
Q3255
95-th percentile359
Maximum374
Range373
Interquartile range (IQR)254

Descriptive statistics

Standard deviation132.76003
Coefficient of variation (CV)0.98092461
Kurtosis-1.3514863
Mean135.34173
Median Absolute Deviation (MAD)106
Skewness0.41450077
Sum580210
Variance17625.227
MonotonicityNot monotonic
2024-10-01T13:55:46.460649image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1478
34.5%
358 26
 
0.6%
370 22
 
0.5%
357 21
 
0.5%
363 21
 
0.5%
360 20
 
0.5%
361 19
 
0.4%
350 19
 
0.4%
359 19
 
0.4%
355 19
 
0.4%
Other values (363) 2623
61.2%
ValueCountFrequency (%)
1 1478
34.5%
2 5
 
0.1%
3 7
 
0.2%
4 4
 
0.1%
5 5
 
0.1%
6 7
 
0.2%
7 11
 
0.3%
8 2
 
< 0.1%
9 2
 
< 0.1%
10 9
 
0.2%
ValueCountFrequency (%)
374 5
 
0.1%
373 10
0.2%
372 14
0.3%
371 12
0.3%
370 22
0.5%
369 14
0.3%
368 7
 
0.2%
367 15
0.3%
366 11
0.3%
365 12
0.3%

total_quantity
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1757
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1291.1787
Minimum1
Maximum220600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:47.080647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile46
Q1162
median386
Q31001
95-th percentile3440.5
Maximum220600
Range220599
Interquartile range (IQR)839

Descriptive statistics

Standard deviation6476.3168
Coefficient of variation (CV)5.0158176
Kurtosis520.83429
Mean1291.1787
Median Absolute Deviation (MAD)286
Skewness20.243455
Sum5535283
Variance41942679
MonotonicityNot monotonic
2024-10-01T13:55:47.441670image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 19
 
0.4%
72 18
 
0.4%
48 17
 
0.4%
96 17
 
0.4%
108 16
 
0.4%
74 15
 
0.3%
144 15
 
0.3%
100 14
 
0.3%
24 14
 
0.3%
138 13
 
0.3%
Other values (1747) 4129
96.3%
ValueCountFrequency (%)
1 9
0.2%
2 3
 
0.1%
3 5
0.1%
4 2
 
< 0.1%
5 5
0.1%
6 5
0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
10 4
0.1%
11 3
 
0.1%
ValueCountFrequency (%)
220600 1
< 0.1%
170278 1
< 0.1%
125893 1
< 0.1%
124216 1
< 0.1%
108076 1
< 0.1%
87829 1
< 0.1%
87167 1
< 0.1%
75824 1
< 0.1%
69637 1
< 0.1%
63551 1
< 0.1%

total_unique_items
Real number (ℝ)

HIGH CORRELATION 

Distinct346
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.930488
Minimum1
Maximum1737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:47.879724image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q117
median38
Q380
95-th percentile203
Maximum1737
Range1736
Interquartile range (IQR)63

Descriptive statistics

Standard deviation85.757359
Coefficient of variation (CV)1.3414157
Kurtosis78.30722
Mean63.930488
Median Absolute Deviation (MAD)26
Skewness6.1435101
Sum274070
Variance7354.3246
MonotonicityNot monotonic
2024-10-01T13:55:48.277578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 89
 
2.1%
23 80
 
1.9%
13 78
 
1.8%
16 77
 
1.8%
11 75
 
1.7%
19 68
 
1.6%
14 68
 
1.6%
8 66
 
1.5%
6 66
 
1.5%
7 65
 
1.5%
Other values (336) 3555
82.9%
ValueCountFrequency (%)
1 89
2.1%
2 55
1.3%
3 45
1.0%
4 61
1.4%
5 63
1.5%
6 66
1.5%
7 65
1.5%
8 66
1.5%
9 62
1.4%
10 56
1.3%
ValueCountFrequency (%)
1737 1
< 0.1%
1507 1
< 0.1%
1339 1
< 0.1%
1091 1
< 0.1%
1084 1
< 0.1%
712 1
< 0.1%
654 1
< 0.1%
646 1
< 0.1%
606 1
< 0.1%
593 1
< 0.1%

total_items
Real number (ℝ)

HIGH CORRELATION 

Distinct471
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.945883
Minimum1
Maximum5485
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:48.605593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q118.5
median44
Q3103
95-th percentile323.7
Maximum5485
Range5484
Interquartile range (IQR)84.5

Descriptive statistics

Standard deviation201.6959
Coefficient of variation (CV)2.1243248
Kurtosis257.87163
Mean94.945883
Median Absolute Deviation (MAD)32
Skewness12.625668
Sum407033
Variance40681.235
MonotonicityNot monotonic
2024-10-01T13:55:48.940590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 78
 
1.8%
1 75
 
1.7%
12 66
 
1.5%
6 65
 
1.5%
11 63
 
1.5%
9 63
 
1.5%
16 63
 
1.5%
18 62
 
1.4%
23 60
 
1.4%
21 60
 
1.4%
Other values (461) 3632
84.7%
ValueCountFrequency (%)
1 75
1.7%
2 49
1.1%
3 38
0.9%
4 56
1.3%
5 56
1.3%
6 65
1.5%
7 60
1.4%
8 59
1.4%
9 63
1.5%
10 52
1.2%
ValueCountFrequency (%)
5485 1
< 0.1%
5041 1
< 0.1%
3857 1
< 0.1%
2617 1
< 0.1%
2615 1
< 0.1%
2499 1
< 0.1%
2269 1
< 0.1%
2052 1
< 0.1%
1773 1
< 0.1%
1726 1
< 0.1%
Distinct4162
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
Minimum2009-12-01 09:55:00
Maximum2010-12-09 20:01:00
2024-10-01T13:55:49.292592image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:49.655474image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4190
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
Minimum2009-12-01 07:45:00
Maximum2010-12-09 16:08:00
2024-10-01T13:55:50.020479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:50.407475image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1118
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size33.6 KiB
2024-10-01T13:55:52.058635image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1182645
Min length4

Characters and Unicode

Total characters21942
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique533 ?
Unique (%)12.4%

Sample

1st row15056BL
2nd row84558A
3rd row21211
4th row16156S
5th row20886
ValueCountFrequency (%)
85123a 121
 
2.8%
21034 76
 
1.8%
20914 64
 
1.5%
21232 62
 
1.4%
post 61
 
1.4%
20725 59
 
1.4%
20685 58
 
1.4%
21754 47
 
1.1%
15036 39
 
0.9%
22423 36
 
0.8%
Other values (1108) 3664
85.5%
2024-10-01T13:55:53.561636image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5314
24.2%
1 3605
16.4%
0 2254
10.3%
7 1653
 
7.5%
5 1591
 
7.3%
8 1523
 
6.9%
4 1365
 
6.2%
6 1315
 
6.0%
3 1277
 
5.8%
9 1233
 
5.6%
Other values (19) 812
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 5314
24.2%
1 3605
16.4%
0 2254
10.3%
7 1653
 
7.5%
5 1591
 
7.3%
8 1523
 
6.9%
4 1365
 
6.2%
6 1315
 
6.0%
3 1277
 
5.8%
9 1233
 
5.6%
Other values (19) 812
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 5314
24.2%
1 3605
16.4%
0 2254
10.3%
7 1653
 
7.5%
5 1591
 
7.3%
8 1523
 
6.9%
4 1365
 
6.2%
6 1315
 
6.0%
3 1277
 
5.8%
9 1233
 
5.6%
Other values (19) 812
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 5314
24.2%
1 3605
16.4%
0 2254
10.3%
7 1653
 
7.5%
5 1591
 
7.3%
8 1523
 
6.9%
4 1365
 
6.2%
6 1315
 
6.0%
3 1277
 
5.8%
9 1233
 
5.6%
Other values (19) 812
 
3.7%

Interactions

2024-10-01T13:55:36.545053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:14.808038image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:17.576934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:20.884542image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:23.685661image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:27.209144image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:30.350704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:33.963644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:36.855457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:14.970381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:17.788402image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:21.448028image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:23.965554image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:27.852118image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:30.761711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:34.176663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:37.112452image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:15.175076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:18.575111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:21.766902image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:24.214853image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:28.027918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:31.348702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:34.371662image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:37.494456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:15.397385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:18.965739image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:22.061464image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:24.801934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:28.208525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:31.882705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:34.569659image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:37.739453image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:15.719808image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:19.529912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:22.344695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:25.567644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:28.381577image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:32.330702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:34.776661image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:38.048452image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:16.713970image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:19.899699image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:22.612611image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:25.863791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:28.562706image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:32.606705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:35.244697image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:38.257454image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:17.182521image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:20.200628image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:22.846035image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:26.482356image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:29.479705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:33.172704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:36.015698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:38.477397image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:17.409111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:20.544627image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:23.179369image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:26.766040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:29.912703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:33.499702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-01T13:55:36.296695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-10-01T13:55:53.802675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
customer_idfrequencylast_visitmonataryrecencytotal_itemstotal_quantitytotal_unique_items
customer_id1.000-0.002-0.017-0.084-0.0090.001-0.0680.001
frequency-0.0021.000-0.5260.8280.8870.7440.7750.672
last_visit-0.017-0.5261.000-0.461-0.538-0.469-0.433-0.431
monatary-0.0840.828-0.4611.0000.7400.7940.9380.744
recency-0.0090.887-0.5380.7401.0000.6640.6890.606
total_items0.0010.744-0.4690.7940.6641.0000.7680.985
total_quantity-0.0680.775-0.4330.9380.6890.7681.0000.723
total_unique_items0.0010.672-0.4310.7440.6060.9850.7231.000

Missing values

2024-10-01T13:55:38.754398image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-01T13:55:39.597803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idmonataryfrequencylast_visitrecencytotal_quantitytotal_unique_itemstotal_itemslast_purchasefirst_purchasemost_purchase_item
012346.00169.3621651192424242010-06-28 13:53:002010-03-02 13:08:0015056BL
112347.001323.32233882870712010-12-07 14:57:002010-10-31 14:20:0084558A
212348.00222.16174137320202010-09-27 14:59:002010-09-27 14:59:0021211
312349.002671.14343182993901022010-10-28 08:23:002010-04-29 13:20:0016156S
412351.00300.93111126121212010-11-29 15:23:002010-11-29 15:23:0020886
512352.00343.802111718818182010-11-29 10:07:002010-11-12 10:20:0021121
612353.00317.76144119220202010-10-27 12:44:002010-10-27 12:44:0020617
712355.00488.211203130322222010-05-21 11:59:002010-05-21 11:59:0020818
812356.003562.2531645182668842010-11-24 12:24:002010-10-11 09:42:0016156S
912357.0012079.99224138791651652010-11-16 14:29:002010-11-16 10:05:0010002
customer_idmonataryfrequencylast_visitrecencytotal_quantitytotal_unique_itemstotal_itemslast_purchasefirst_purchasemost_purchase_item
427718277.001069.674339838148562010-11-07 15:52:002010-08-02 10:26:0015056BL
427818278.00240.3014017415152010-10-31 12:13:002010-10-31 12:13:0020914
427918279.00231.341155163013132010-07-08 14:48:002010-07-08 14:48:0017003
428018280.00307.55130114920202010-11-10 15:51:002010-11-10 15:51:0021114
428118281.00120.32121319210102010-05-11 10:49:002010-05-11 10:49:0020719
428218283.00641.776182763361582302010-11-22 15:30:002010-02-19 17:16:0020727
428318284.00411.68167149327272010-10-04 11:33:002010-10-04 11:33:0016237
428418285.00377.001296114411112010-02-17 10:24:002010-02-17 10:24:0020802
428518286.001246.43211224860766662010-08-20 11:57:002009-12-16 10:45:0010135
428618287.002295.71418189142676842010-11-22 11:51:002010-05-17 11:55:0022064